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Posted on Thu, 04/11/2019 - 08:53
Learning is a continuous process in life. Even at work, you have to be trained on the latest skills as they emerge. Adaptive learning is a model that goes against the usual one-size-fits-all approach to learning. Under adaptive learning, each individual has a tailored learning experience. This takes all the factors of the individual into consideration such as their weaknesses, strengths, and patterns of engagement. This is an approach that changes in real time to reflect the learner’s abilities and adapt to them.
In order for adaptive learning to be up-to-date and relevant to a learner’s needs, it often utilizes the power of artificial intelligence or AI. The system is able to understand the unique needs of the learner by analyzing their learning patterns based on previous interactions with the system. AI is a mix of the following: machine learning, educational theory, cognitive science, and predictive analytics. This means that the data also comes from previous research done on the topic. Using complex AI algorithms, the adaptive learning platform adapts to your learning needs.
Most of the learning that goes on in the world puts people together, teaching them the same things and testing them together. This is true even for some eLearning platforms. Although this method has been in existence for quite some time, it’s not completely reliable. The problem with using a standardized course outline is that it wants people to think the same way, which is rather impossible. People are different and what works for one person may not necessarily work for someone else. Everyone has different learning preferences. On this note, adaptive learning is the answer to a new learning experience that makes everyone a winner by focusing on their strengths to instill the same knowledge.
Companies need to keep their employees up-to-date with market trends if they want to gain a competitive advantage. Here are some of the ways in which adaptive learning can be used in the workplace:
In learning, there’s always the addition of new material. The new information may be a result of emerging trends in the sector or updated changes in the training manual. In most cases, these changes are needed to ensure that what the learner studies is relevant to the industry. Traditionally, the management would just add new material to the existing online learning platform. The problem with this approach is that there’s always a possibility that some learners have seen that information before. Therefore, it would only be repetitive for them. Such an outcome creates a state of confusion.
This is where adaptive learning in employee training makes all the difference. Instead of just adding new content for the learners, the system decides which learners should see the new content and what content they should focus on. In most cases, it chooses the learners that haven’t seen the content before, getting rid of unneeded repetition.
The traditional approach to learning can be unfair and unequal. This is because the system trains both experienced and novice workers using the same manual. If the training is more practical-based, the experienced workers may have an unfair advantage over the rookie recruits. As a result, the performance outcomes may not show the true level of skills or expertise of the novice workers.
However, with adaptive learning, everyone is catered to. Every person has a unique learning path which provides them with an opportunity to learn and master concepts that are relevant to them. It does not discriminate between an expert and a novice as the progress is different for each person. A personalized learning approach ensures that, at the end of the day, everyone is moving forward and new skills are learned and mastered.
In the corporate world, there are a series of standardized yearly tests that every worker must take in order to make sure that they are up-to-date with the industry trends and needs. The problem with such tests is that they are not very engaging. They are often a check-the-box assessment where employees just have to pass the test to prove that they have mastered the course content. A worker can simply pass what he or she knows every year without learning anything new.
One of the benefits of adaptive learning is that it makes employee training more compelling and productive. Adaptive learning uses a question-based approach. This probes what the learner knows and then uses the data gathered to create the learning path that they will take. A question-based approach builds confidence as it gauges what you know and then aims to increase the knowledge from there. The data gathered is also important in being able to track the learning progress when there is an update to the learning material.
The problem with traditional training methods is that it can take longer than usual for someone to master a new skill. This is because the system uses the same method to teach all learners. The dilemma with such an approach is that it doesn’t help the weak learners improve.
Adaptive learning benefits both the workers and management by saving time. The system focuses on the weaknesses of learners and works on improving them. It also leaves out that which the learner knows and as a result, it takes a shorter time for a worker to understand a specific subject. That allows the organization to be more efficient and meet its goals much faster.
Using adaptive learning in employee training can maximize efficiency and allow you to achieve your organizational goals within a short period of time. Adaptive learning benefits workers by allowing them to improve upon their weaknesses. Overall, this makes the training process more interesting and effective.
By Designing Digitally, Inc.
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